1. Field of the Invention
The present invention relates to an apparatus and method for extracting spatio-temporal feature and detecting video copy based on the same; and, more particularly, to an apparatus and method for extracting spatio-temporal feature and determining whether or not video is copied based on the spatio-temporal feature in a broadcasting communication system.
2. Description of Related Art
A large broadcasting contents made in Korea, which is a point of the Korean wave, is illegally circulated in abroad as well as in Korean through the Internet. The illegal circulation costs the great loss to the contents provider. Especially, as the merge of broadcast and communication is accelerated, a scale of copyright infringement has been enlarged. Accordingly, the government and the copyright protection organization concentrate on various efforts for preventing from the illegal copy of the contents by revising the copyright law and by enforcing control and punishment of an illegal work. Especially, the complete revised copyright law includes an article to make it mandatory for an Online Service Provider (OSP) of special type recording media such as Peer-to-peer (P2P), web storage, and the like to perform ‘a technological action (filtering) for cutting off transmission of the illegal work’.
Filtering technology of an illegal work cuts off illegal Internet transmission of a copyright infringement by determining whether a video, music, a game, and the like circulated in on-line is an illegal work or not. The filtering technology of an illegal work should have a contents identification function. That is, the filtering technology extracts features that are unique characteristics of the contents, and determines whether or not the illegal contents is the same as the rightful contents by comparing the features of the rightful contents and the illegal contents. Here, what feature is used acts important role to decide performance of filtering technology that is cutoff rate of the illegal work.
The filtering technology may greatly be divided by a text filtering scheme based on a title, a string, an extension, and the like; a filtering scheme using comparison of a unique hash value existing in a file; and a content-based filtering scheme using audio/video recognition technology. The text-filtering scheme establishes the specified restrict words and does not allow the restrict words to be used in searching. The text-filtering scheme may be classified by a title filtering, a string comparing scheme, an extension filtering, and the like. The text-filtering scheme establishing the specified restrict word may easily be incapacitated, because various roundabout and evasion methods are possible.
The content-based filtering scheme, which is different from the text-filtering scheme, does not use a key word for searching. The content-based filtering scheme extracts a unique pattern of contents as features and performs filtering based on the feature. Also, even though a file including contents is copied, the contents itself is not easily changed in a different way from a filtering scheme using comparison of hash values. Therefore, the content-based filtering scheme is recognized by filtering technology that has the most superior performance.
Also, a content-based video searching algorithm and a video copy detection algorithm through video feature extraction may be classified into a method using a global feature of each video frame; a method using the mixed spatio-temporal feature; and a method using a local feature.
A color histogram based searching method uses a histogram of the global screen color that is distributed in every video frame as features. However, the color histogram based searching method may be very sensitive to a little color change due to conversion of a video format (e.g. MPEG, AVI, WMV, and the like) or visual quality, because the color histogram based searching method does not consider spatial position information of colors in the frame.
Since most of content-based video searching and detection algorithms extracts features on frame-by-frame basis and compares the features of all frames, the content-based video searching and detection methods would need a lot of computation time in the case of vast size of database. Recently, the size and volume of videos, such as a movie and a broadcasting content, are rapidly increasing. Accordingly, processing time is very important factor to improve performance of video copy detection.
Also, a conventional detection algorithm considers a few of edit effects that are applied to illegal copy video. In recent, a general user can easily apply various video edition effects to distributed videos like User Created Contents (UCC) edition according to active distribution of video edition software. Therefore, considering these situations, there is a need that a feature extraction and copy detection method is robust to video edition effects and has a high calculation speed for fast computation of mass video data.